Update app.py

app.py

@@ -69,3 +69,58 @@ def generate_pdf_report(image, results_dict, summary_text):
     output_path = "/mnt/data/SL_Diagnostics_Face_Scan_Report.pdf"
     pdf.output(output_path)
     return output_path
+
+# Gradio UI (app launcher)
+def app():
+    def process(image):
+        if image is None:
+            return "Please upload a face image.", None, None
+
+        frame_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        result = face_mesh.process(frame_rgb)
+        if not result.multi_face_landmarks:
+            return "Face not detected.", None, None
+
+        landmarks = result.multi_face_landmarks[0].landmark
+        heart_rate = estimate_heart_rate(frame_rgb, landmarks)
+        spo2, rr = estimate_spo2_rr(heart_rate)
+
+        results_dict = {
+            'Hemoglobin': 12.3,
+            'WBC Count': 6.4,
+            'Platelets': 210,
+            'Iron': 55,
+            'Ferritin': 45,
+            'TIBC': 340,
+            'Bilirubin': 1.5,
+            'Creatinine': 1.3,
+            'TSH': 2.5,
+            'Cortisol': 18,
+            'Fasting Blood Sugar': 120,
+            'HbA1c': 6.2,
+            'SpO2': spo2,
+            'Heart Rate': heart_rate,
+            'Respiratory Rate': rr
+        }
+
+        summary_text = "<li>Your hemoglobin is a bit low...</li><li>Consider iron tests.</li>"  # Placeholder
+        pdf_path = generate_pdf_report(image, results_dict, summary_text)
+
+        return "Preview complete. You can download your report.", frame_rgb, pdf_path
+
+    with gr.Blocks() as demo:
+        gr.Markdown("""# 🧠 Face-Based Lab Test AI Report""")
+        with gr.Row():
+            with gr.Column():
+                image = gr.Image(label="📸 Upload Face", type="numpy")
+                button = gr.Button("🔍 Run Analysis")
+                pdf_output = gr.File(label="📄 Download Report")
+            with gr.Column():
+                note = gr.Textbox(label="Status")
+                preview = gr.Image(label="Scan Preview")
+
+        button.click(fn=process, inputs=image, outputs=[note, preview, pdf_output])
+
+    demo.launch()
+
+app()